Brian Lau

Value Representations in the Primate Striatum during Matching Behavior

Choosing the most valuable course of action requires knowing the outcomes associated with the available alternatives. The striatum may be important for representing the values of actions. We examined this in monkeys performing an oculomotor choice task. The activity of phasically active neurons (PANs) in the striatum covaried with two classes of information: action-values and chosen-values. Action-value PANs were correlated with value estimates for one of the available actions, and these signals were frequently observed before movement execution. Chosen-value PANs were correlated with the value of the action that had been chosen, and these signals were primarily observed later in the task, immediately before or persistently after movement execution. These populations may serve distinct functions mediated by the striatum: some PANs may participate in choice by encoding the values of the available actions, while other PANs may participate in evaluative updating by encoding the reward value of chosen actions.

Action and Outcome Encoding in the Primate Caudate Nucleus

The basal ganglia appear to have a central role in reinforcement learning. Previous experiments, focusing on activity preceding movement execution, support the idea that dorsal striatal neurons bias action selection according to the expected values of actions. However, many phasically active striatal neurons respond at a time too late to initiate or select movements. Given the data suggesting a role for the basal ganglia in reinforcement learning, postmovement activity may therefore reflect evaluative processing important for learning the values of actions. To better understand these postmovement neurons, we determined whether individual striatal neurons encode information about saccade direction, whether a reward had been received, or both. We recorded from phasically active neurons in the caudate nucleus while monkeys performed a probabilistically rewarded delayed saccade task. Many neurons exhibited peak responses after saccade execution (77 of 149) that were often tuned for the direction of the preceding saccade (61 of 77). Of those neurons responding during the reward epoch, one subset showed direction tuning for the immediately preceding saccade (43 of 60), whereas another subset responded differentially on rewarded versus unrewarded trials (35 of 60). We found that there was relatively little overlap of these properties in individual neurons. The encoding of action and outcome was performed by largely separate populations of caudate neurons that were active after movement execution. Thus, striatal neurons active primarily after a movement appear to be segregated into two distinct groups that provide complimentary information about the outcomes of actions.

Dopaminergic Drugs Modulate Learning Rates and Perseveration in Parkinson's Patients in a Dynamic Foraging Task

Making appropriate choices often requires the ability to learn the value of available options from experience. Parkinsons disease is characterized by a loss of dopamine neurons in the substantia nigra, neurons hypothesized to play a role in reinforcement learning. Although previous studies have shown that Parkinsons patients are impaired in tasks involving learning from feedback, they have not directly tested the widely held hypothesis that dopamine neuron activity specifically encodes the reward prediction error signal used in reinforcement learning models. To test a key prediction of this hypothesis, we fit choice behavior from a dynamic foraging task with reinforcement learning models and show that treatment with dopaminergic drugs alters choice behavior in a manner consistent with the theory. More specifically, we found that dopaminergic drugs selectively modulate learning from positive outcomes. We observed no effect of dopaminergic drugs on learning from negative outcomes. We also found a novel dopamine-dependent effect on decision making that is not accounted for by reinforcement learning models: perseveration in choice, independent of reward history, increases with Parkinsons disease and decreases with dopamine therapy.

The primate amygdala combines information about space and value

A stimulus predicting reinforcement can trigger emotional responses, such as arousal, and cognitive ones, such as increased attention toward the stimulus. Neuroscientists have long appreciated that the amygdala mediates spatially nonspecific emotional responses, but it remains unclear whether the amygdala links motivational and spatial representations. To test whether amygdala neurons encode spatial and motivational information, we presented reward-predictive cues in different spatial configurations to monkeys and assessed how these cues influenced spatial attention. Cue configuration and predicted reward magnitude modulated amygdala neural activity in a coordinated fashion. Moreover, fluctuations in activity were correlated with trial-to-trial variability in spatial attention. Thus, the amygdala integrates spatial and motivational information, which may influence the spatial allocation of cognitive resources. These results suggest that amygdala dysfunction may contribute to deficits in cognitive processes normally coordinated with emotional responses, such as the directing of attention toward the location of emotionally relevant stimuli.

Normal and pathological gait: what we learn from Parkinson's disease

Gait and balance disorders represent a major therapeutic challenge in Parkinsons disease (PD). These symptoms respond poorly to dopaminergic treatments, except in the early phase of the disease. Currently, no other treatment is particularly efficient and rehabilitation appears to be the most effective approach. Since these gait and balance deficits are resistant to dopaminergic drugs, their occurrence could be related to the development of extradopaminergic lesions in PD patients. We provide a comprehensive description of the clinical features of gait and balance disorders in PD. We also highlight the brain networks involved in gait and balance control in animals and humans with a particular focus on the relevant structures in the context of PD, such as the mesencephalic locomotor region. We also review other neuronal systems that may be involved in the physiopathology of gait and balance disorders in PD (noradrenergic and serotoninergic systems, cerebellum and cortex). In addition, we review recent evidence regarding functional neurosurgery for gait disorders in PD and propose new directions for future therapeutic research.

Computational subunits of visual cortical neurons revealed by artificial neural networks

A crucial step toward understanding visual processing is to obtain a comprehensive description of the relationship between visual stimuli and neuronal responses. Many neurons in the visual cortex exhibit nonlinear responses, making it difficult to characterize their stimulus–response relationships. Here, we recorded the responses of primary visual cortical neurons of the cat to spatiotemporal random-bar stimuli and trained artificial neural networks to predict the response of each neuron. The random initial connections in the networks consistently converged to regular patterns. Analyses of these connection patterns showed that the response of each complex cell to the random-bar stimuli could be well approximated by the sum of a small number of subunits resembling simple cells. The direction selectivity of each complex cell measured with drifting gratings was also well predicted by the combination of these subunits, indicating the generality of the model. These results are consistent with a simple functional model for complex cells and demonstrate the usefulness of the neural network method for revealing the stimulus–response transformations of nonlinear neurons.

The integrative role of the pedunculopontine nucleus in human gait

The brainstem pedunculopontine nucleus has a likely, although unclear, role in gait control, and is a potential deep brain stimulation target for treating resistant gait disorders. These disorders are a major therapeutic challenge for the ageing population, especially in Parkinsons disease where gait and balance disorders can become resistant to both dopaminergic medication and subthalamic nucleus stimulation. Here, we present electrophysiological evidence that the pedunculopontine and subthalamic nuclei are involved in distinct aspects of gait using a locomotor imagery task in 14 patients with Parkinsons disease undergoing surgery for the implantation of pedunculopontine or subthalamic nuclei deep brain stimulation electrodes. We performed electrophysiological recordings in two phases, once during surgery, and again several days after surgery in a subset of patients. The majority of pedunculopontine nucleus neurons (57%) recorded intrasurgically exhibited changes in activity related to different task components, with 29% modulated during visual stimulation, 41% modulated during voluntary hand movement, and 49% modulated during imaginary gait. Pedunculopontine nucleus local field potentials recorded post-surgically were modulated in the beta and gamma bands during visual and motor events, and we observed alpha and beta band synchronization that was sustained for the duration of imaginary gait and spatially localized within the pedunculopontine nucleus. In contrast, significantly fewer subthalamic nucleus neurons (27%) recorded intrasurgically were modulated during the locomotor imagery, with most increasing or decreasing activity phasically during the hand movement that initiated or terminated imaginary gait. Our data support the hypothesis that the pedunculopontine nucleus influences gait control in manners extending beyond simply driving pattern generation. In contrast, the subthalamic nucleus seems to control movement execution that is not likely to be gait-specific. These data highlight the crucial role of these two nuclei in motor control and shed light on the complex functions of the lateral mesencephalus in humans.

Reward expectation differentially modulates attentional behavior and activity in visual area V4

Neural activity in visual area V4 is enhanced when attention is directed into neuronal receptive fields. However, the source of this enhancement is unclear, as most physiological studies have manipulated attention by changing the absolute reward associated with a particular location as well as its value relative to other locations. We trained monkeys to discriminate the orientation of two stimuli presented simultaneously in different hemifields while we independently varied the reward magnitude associated with correct discrimination at each location. Behavioral measures of attention were controlled by the relative value of each location. By contrast, neurons in V4 were consistently modulated by absolute reward value, exhibiting increased activity, increased gamma-band power and decreased trial-to-trial variability whenever receptive field locations were associated with large rewards. These data challenge the notion that the perceptual benefits of spatial attention rely on increased signal-to-noise in V4. Instead, these benefits likely derive from downstream selection mechanisms.

Complexity and Competition in Appetitive and Aversive Neural Circuits

Decision-making often involves using sensory cues to predict possible rewarding or punishing reinforcement outcomes before selecting a course of action. Recent work has revealed complexity in how the brain learns to predict rewards and punishments. Analysis of neural signaling during and after learning in the amygdala and orbitofrontal cortex, two brain areas that process appetitive and aversive stimuli, reveals a dynamic relationship between appetitive and aversive circuits. Specifically, the relationship between signaling in appetitive and aversive circuits in these areas shifts as a function of learning. Furthermore, although appetitive and aversive circuits may often drive opposite behaviors – approaching or avoiding reinforcement depending upon its valence – these circuits can also drive similar behaviors, such as enhanced arousal or attention; these processes also may influence choice behavior. These data highlight the formidable challenges ahead in dissecting how appetitive and aversive neural circuits interact to produce a complex and nuanced range of behaviors.

Emergence of un-correlated common-mode oscillations in the sensory cortex

Abstract Simultaneous EEG recordings from various cortical areas indicate the presence of common-mode, spatially coherent oscillations. These oscillations are characterized by a common wave form with a spatially distributed pattern of amplitude modulation (AM). We observe highly reproducible AM patterns across spatially separated channels within various areas, yet the temporal correlations between the channels are low. In the framework of the present research, a nonlinear, spatially distributed dynamical model of neuronal populations (KIII) is used for the interpretation of the observed spatial coherence. The theoretical findings are in good agreement with experiments performed with chronically implanted rabbits.